An adaptive coordinated control method for multi-component injection molding

Abstract

This invention discloses an adaptive cooperative control method for multi-component injection molding, relating to the field of multi-component injection molding technology. It aims to solve the technical problem in existing multi-component injection molding methods that rely on indirect temperature control and cannot accurately capture the optimal viscoelastic welding window at the interface. The method includes: injecting a first component material to form a first molded body with surfaces to be joined; applying interfacial activation energy to the surfaces to be joined, causing the surface material of the surfaces to transition to a viscoelastic state; during the application of the interfacial activation energy, emitting an acoustic wave signal to the surfaces to be joined through a solid-state dielectric wave sensing device and receiving the response acoustic wave signal propagating through the surfaces; and determining the appropriate response acoustic wave signal. This invention has the advantages of directly sensing the molecular chain entanglement state based on acoustic parameters, achieving closed-loop adaptive cooperative control, and significantly improving welding strength and optical clarity.

Description

Technical Field

[0001] This invention relates to the field of multi-component injection molding technology, and more specifically, to an adaptive collaborative control method for multi-component injection molding. Background Technology

[0002] Multi-component injection molding is a technology that uses sequential injection to form a single molded product with a multi-layered structure or multiple integrated functions from two or more polymer materials with different properties. This technology is widely used in the manufacturing of high-end products such as automotive interior ambient lighting panels, which require optical transmittance, light-blocking patterns, and surface tactile properties.

[0003] In the sequential injection process of multi-component injection molding, after the first component material is injected and cools and solidifies in the mold cavity to form the first molded body, the temperature of the surface to be bonded has dropped significantly. The surface material is in a glassy or near-glassy frozen state with highly entangled molecular chains. If the second component material is injected directly at this time, the molecular chains of the second component material cannot diffuse and entangle sufficiently with those of the first component material due to the extremely low mobility of the molecular chains on the surface to be bonded of the first molded body. This results in insufficient interfacial bonding strength between the two components, making it prone to interfacial delamination failure during subsequent use. At the same time, if the second component material impacts the low-temperature surface to be bonded under high pressure and high speed, it will also cause erosion deformation of the surface microstructure. For ambient light panels containing precision light-shielding patterns, this will directly lead to pattern blurring and light leakage defects.

[0004] To enhance the interfacial bonding strength between two components, existing technologies typically employ methods such as continuous heating in hot runners, increased mold temperature, or pre-heating the surface of the first molded part with infrared radiation. This reheats and softens the surface material of the surfaces to be joined, causing it to transition from a glassy state to a viscoelastic state, thereby improving the mobility of the surface molecular chains. However, these activation methods are all based on indirect control using temperature parameters, i.e., inferring whether the interfacial state is suitable for welding by measuring or controlling the heating temperature. Since the viscoelastic transition of polymer materials depends not only on temperature but also on a complex interplay of factors such as molecular weight distribution, filler content, cooling rate history, and inter-mold fluctuations, relying solely on temperature parameters cannot accurately characterize the true molecular chain entanglement state and degree of viscoelastic transition of the surface material to be joined. This results in either insufficient activation, where the surface molecular chain mobility remains low, leading to limited improvement in weld strength, or excessive activation, where the surface material undergoes irreversible viscous flow and is washed away and displaced during the injection of the second component, causing pattern distortion. Therefore, we propose an adaptive synergistic control method for multi-component injection molding. Summary of the Invention

[0005] The purpose of this invention is to provide an adaptive collaborative control method for multi-component injection molding, so as to solve the technical problem that existing multi-component injection molding relies on indirect temperature control and cannot accurately capture the optimal viscoelastic weld window of the interface.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: an adaptive collaborative control method for multi-component injection molding, comprising: Inject the first component material to form a first molded body with the surfaces to be joined; Interfacial activation energy is applied to the surfaces of the first molded body to be joined, causing the surface material of the surfaces to be joined to transform into a viscoelastic state; During the process of applying interfacial activation energy, a solid-state dielectric wave sensing device transmits acoustic wave signals to the surface to be connected and receives the response acoustic wave signals propagating through the surface to be connected. Based on the response acoustic signal, characteristic acoustic parameters reflecting the molecular chain entanglement state of the surface material to be connected are extracted. The characteristic acoustic parameters are compared with preset acoustic parameter thresholds that characterize the optimal activation state. When the characteristic acoustic parameters reach the acoustic parameter thresholds, it is determined that the surface to be connected has reached the optimal activation state. The following operations are performed simultaneously: the application of interfacial activation energy to the surfaces to be joined is terminated, and the injection of the second component material is triggered, so that the second component material contacts and fuses with the surfaces to be joined in the optimal activation state.

[0007] Preferably, the solid-state dielectric wave sensing device is a piezoelectric microelectromechanical system ultrasonic transceiver array, which transmits acoustic wave signals to the surface to be connected and receives response acoustic wave signals propagating through the surface to be connected, including: The ultrasonic transverse and longitudinal waves of the piezoelectric microelectromechanical system are emitted to the surface to be connected by an ultrasonic transceiver array, and the response ultrasonic signals propagating through the near-surface region of the surface to be connected are received.

[0008] Preferably, the extraction of characteristic acoustic parameters reflecting the entanglement state of molecular chains in the surface material to be joined includes: The ultrasonic velocity change rate and acoustic attenuation dispersion characteristics are extracted from the response ultrasonic signal. Based on the pre-established acoustic parameter-molecular chain entanglement mapping relationship, the molecular chain entanglement degree of the surface material to be joined is obtained by inversion, and the molecular chain entanglement degree is used as a characteristic acoustic parameter.

[0009] Preferably, the preset acoustic parameter threshold for characterizing the optimal activation state is a molecular chain entanglement threshold range, which corresponds to a viscoelastic state window where the molecular chains of the surface material to be connected are partially unentangled but have not undergone irreversible flow. When the molecular chain entanglement degree obtained by inversion falls within the molecular chain entanglement degree threshold range, it is determined that the surface to be connected has reached the optimal activation state.

[0010] Preferably, applying interfacial activation energy to the surfaces to be joined of the first molded body includes: A modulated laser pulse energy is applied to the surfaces to be joined. The pulse waveform of the laser pulse energy is adaptively set according to the pattern characteristics of the surfaces to be joined. The pulse waveform includes pulse width and peak power parameters.

[0011] Preferably, when the surface to be connected includes a fine line region with a line width less than a preset value and a surface region with a line width greater than a preset value, a first pulse waveform is applied to the fine line region and a second pulse waveform is applied to the surface region. The pulse width of the first pulse waveform is less than the pulse width of the second pulse waveform, and the peak power of the first pulse waveform is greater than the peak power of the second pulse waveform.

[0012] Preferably, the trigger injection of the second component material includes: In the initial stage of injection, a peristaltic filling rate curve is used to make the melt front of the second component material contact the surface to be joined in a laminar flow state, thereby achieving molecular-level diffusion welding.

[0013] An adaptive collaborative control system for multi-component injection molding includes: The first injection module is used to inject the first component material and mold it into a first molded body with a surface to be connected. The activation module is used to apply interfacial activation energy to the surfaces to be joined of the first molded body, so that the surface material of the surfaces to be joined is transformed into a viscoelastic state. The sensing module is used to emit acoustic wave signals to the surface to be connected during the application of interface activation energy, and to receive the response acoustic wave signals propagating through the surface to be connected. The parameter extraction module is used to extract characteristic acoustic parameters that reflect the entanglement state of molecular chains of the surface material to be connected, based on the response acoustic wave signal. The determination module is used to compare the characteristic acoustic parameters with preset acoustic parameter thresholds that characterize the optimal activation state. When the characteristic acoustic parameters reach the acoustic parameter thresholds, it is determined that the surface to be connected has reached the optimal activation state. The collaborative execution module is used to synchronously perform the following operations: terminate the application of interfacial activation energy to the surfaces to be joined, and trigger the injection of the second component material, so that the second component material contacts and fuses with the surfaces to be joined in the optimal activation state.

[0014] An electronic device includes a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement an adaptive collaborative control method for multi-component injection molding.

[0015] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements an adaptive cooperative control method for multi-component injection molding.

[0016] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention uses a solid-state dielectric wave sensing device to emit acoustic signals to the surface to be joined and receive the response acoustic signals. Characteristic acoustic parameters reflecting the entanglement state of the molecular chains in the surface material are extracted from the response acoustic signals. This transforms the reliance on indirect temperature estimation for determining the degree of interface activation from traditional methods to direct characterization using acoustic parameters. Because the propagation speed and attenuation characteristics of ultrasound in the near-surface region of polymers are highly sensitive to changes in the entanglement and de-entanglement states of molecular chains, this method can penetrate the surface layer to directly obtain physical information about changes in the aggregated structure of molecular chains. This fundamentally solves the inherent defect that temperature measurements cannot accurately reflect the degree of viscoelastic state transition, achieving real-time, online, and non-destructive sensing of the interface activation state.

[0017] 2. This invention further compares the extracted characteristic acoustic parameters with preset acoustic parameter thresholds representing the optimal activation state. When the characteristic acoustic parameters reach the threshold, it is determined that the surface to be connected has reached the optimal activation state, and the application of interface activation energy and the triggering of the second component material injection are simultaneously terminated. This constructs a closed-loop collaborative control system with the intrinsic physical state of the material as the feedback signal. This closed-loop determination mechanism ensures that the activation endpoint of each module is dynamically determined based on the actual state of the material itself, rather than relying on a fixed heating time or preset delay. It can adaptively compensate for the influence of batch differences in materials, temperature fluctuations between modules, and environmental disturbances on the interface activation process, ensuring that the surface to be connected is in a highly consistent optimal activation window each time the second component material is injected.

[0018] 3. This invention achieves millisecond-level synchronous coordination between the termination of interface activation energy and the injection triggering of the second component material, ensuring that the second component material contacts the surface to be joined precisely at a viscoelastic state window where the molecular chains are partially untangled but have not yet undergone irreversible flow. Because the surface molecular chains below this viscoelastic state window exhibit significantly enhanced mobility, the molecular chains of the second component material can diffuse and entangle fully with the molecular chains of the first component material through a peristaltic filling mechanism, forming a molecular-level fusion interface and significantly improving the bonding strength between the two components. Simultaneously, since the surface material has not yet undergone irreversible flow, no pattern erosion deformation or interface disorder occurs during the fusion process, thus synergistically achieving a balance between high fusion strength and high optical clarity. Attached Figure Description

[0019] Figure 1 This is a flowchart illustrating the adaptive collaborative control method for multi-component injection molding according to the present invention. Figure 2 This is a schematic diagram of the process for applying the interface activation energy according to the present invention; Figure 3 This is a schematic diagram of the process for solid-state dielectric wave sensing and characteristic acoustic parameter extraction of the present invention. Figure 4 This is a schematic diagram illustrating the process of determining the optimal activation state and performing synergistic injection according to the present invention. Detailed Implementation

[0020] To facilitate understanding of the technical solution of the present invention by those skilled in the art, the technical solution of the present invention will now be further described in conjunction with the accompanying drawings.

[0021] Example 1, such as Figures 1-4 As shown, this invention provides an adaptive collaborative control method for multi-component injection molding, the method comprising: Step S1: Inject the first component material to form a first molded body, which has a surface to be joined. Step S2: Apply interfacial activation energy to the surface to be joined of the first molded body to cause the surface material of the surface to be joined to transform into a viscoelastic state. Step S3: During the process of applying interface activation energy, a sound wave signal is emitted to the surface to be connected through a solid dielectric wave sensing device, and a response sound wave signal propagating through the surface to be connected is received. Step S4: Based on the response acoustic signal, extract the characteristic acoustic parameters that reflect the molecular chain entanglement state of the surface material to be connected. Step S5: Compare the characteristic acoustic parameter with a preset acoustic parameter threshold representing the optimal activation state. When the characteristic acoustic parameter reaches the acoustic parameter threshold, it is determined that the surface to be connected has reached the optimal activation state. Step S6: After determining that the surface to be joined has reached the optimal activation state, the following cooperative operation is performed simultaneously: the application of interface activation energy to the surface to be joined is terminated, and the injection of the second component material is triggered so that the second component material contacts and fuses with the surface to be joined in the optimal activation state.

[0022] In this embodiment of the invention, the above steps work together to construct a complete "sensing-decision-execution" closed loop. Step S2, while applying activation energy to the surface to be connected, provides a driving source for the subsequent evolution of the material state. Steps S3 and S4 serve as the sensing links of this closed loop, acquiring the response signals of the material's microscopic state under this driving force in real time and online. Step S5, as the decision-making link, scientifically defines the "optimal" standard of the process window based on the acoustic parameter thresholds in this step. Finally, step S6, as the execution link, achieves precise synchronization between activation termination and subsequent injection on the timeline based on the accurate sensing and decision results.

[0023] Taking a specific application scenario as an example, it is necessary to weld a first component of transparent polycarbonate (PC) to a second component of black polycarbonate / acrylonitrile-butadiene-styrene copolymer alloy (PC / ABS). In step S1, transparent PC is injected into a mold and, after cooling, forms a first molded body with surfaces to be joined. Next, in step S2, interfacial activation energy in the form of pulsed laser is applied to the surfaces of the PC part to be joined, causing an increase in the mobility of the surface PC molecular chain segments, transitioning them to a viscoelastic state. During the activation process, step S3 is simultaneously initiated, where a solid-state dielectric wave sensing device, such as a piezoelectric microelectromechanical system ultrasonic transceiver array, placed inside the mold, continuously transmits acoustic signals to the PC surface and receives the response acoustic signals after propagation near the surface. As the surface PC evolves from the initial state to the viscoelastic state, the degree of deentanglement of its molecular chains increases, which leads to continuous changes in the sound velocity and attenuation characteristics of the ultrasonic waves propagating within it. The signal processing unit in step S4 calculates these changes in real time to obtain the rate of change of sound velocity. and sound wave attenuation and dispersion characteristics Furthermore, it uses a pre-defined mapping function to derive a quantitative index characterizing the molecular chain state, namely the degree of molecular chain entanglement. Step S5 will calculate in real time Value and preset threshold range For comparison, this interval, pre-calibrated experimentally, represents a viscoelastic window where PC molecular chains are partially untangled but not yet irreversibly flowing. When the value gradually decreases with the passage of activation time and falls into this range for the first time, step S5 immediately determines that the surface to be joined has reached the optimal activation state. This determination signal triggers the coordinated operation of step S6 within microseconds: the laser pulse source is instantly turned off, and at the same time, the injection screw of the second component material PC / ABS is triggered to start, injecting molten PC / ABS into the mold cavity at a specific speed curve, so that it can achieve molecular-level diffusion fusion with the PC surface to be joined, which is in the optimal activation state.

[0024] In an optional embodiment, the aforementioned solid-state dielectric wave sensing device is a piezoelectric microelectromechanical system (MEMS) ultrasonic transceiver array, comprising multiple ultrasonic transmitting elements and multiple ultrasonic receiving elements. In step S3, the ultrasonic transmitting elements emit ultrasonic transverse waves and ultrasonic longitudinal waves towards the surface to be connected, and the ultrasonic receiving elements receive the response ultrasonic signals propagating through the near-surface region of the surface to be connected. By simultaneously emitting and analyzing ultrasonic transverse and ultrasonic longitudinal waves, richer information can be obtained from the different sensitivities of the two waves to changes in different material states (such as density and viscoelastic modulus). The wave velocity of the ultrasonic transverse wave is mainly sensitive to the shear modulus of the material, while the wave velocity of the ultrasonic longitudinal wave responds to both the bulk modulus and the shear modulus. During the application of activation energy, the material transitions to a viscoelastic state, and the change in its shear modulus is much more significant than that of its bulk modulus. Therefore, by combining the propagation characteristics of transverse and longitudinal waves, compared with using only a single wave type, it can more sensitively and accurately reflect the core physical characteristics of molecular chain de-entanglement during viscoelastic state transition, thus improving the signal-to-noise ratio and robustness of determining the optimal activation state.

[0025] As a specific implementation, the piezoelectric microelectromechanical system (MEMS) ultrasonic transceiver array is composed of aluminum nitride thin-film piezoelectric microelectromechanical ultrasonic transducers, some of which are functionalized as transmitting elements and others as receiving elements. The transmitting elements generate high-frequency mechanical vibrations due to the piezoelectric effect by applying pulse voltages of a specific frequency (e.g., 10MHz to 50MHz), thereby exciting ultrasonic waves into the solid medium. The receiving elements, based on the inverse piezoelectric effect, convert the received ultrasonic echo mechanical vibration signal into a voltage signal for processing in subsequent step S4. The transmission of transverse and longitudinal ultrasonic waves can be achieved by adjusting the vibration modes of the transducer units, where the transverse vibration mode excites transverse waves and the longitudinal vibration mode excites longitudinal waves; or by designing independent transducer units with different vibration modes and arranging them in a mixed configuration in the array to achieve simultaneous transmission.

[0026] In an optional embodiment, for the aforementioned piezoelectric microelectromechanical system (MEMS) ultrasonic transceiver array, multiple ultrasonic transmitting elements and multiple ultrasonic receiving elements of the array are arranged alternately. The transmitting and receiving surfaces are acoustically coupled to the surface to be connected of the first molded body via a coupling medium layer. This alternating arrangement, such as a staggered layout on a two-dimensional grid where one cell is a transmitting element and its adjacent cells are receiving elements, maximizes the homogenization of the sound field distribution within the sensing area and reduces the blind zone between the transmitter and receiver. This dense and uniform layout ensures high spatial resolution monitoring of the activation state of the entire surface to be connected without blind spots. Using a coupling medium layer to fill the space between the transmitting / receiving surfaces of the array and the surface to be connected of the first molded body effectively removes air from the interface, as sound waves are almost entirely reflected due to the significant impedance difference between the air and solid interfaces. This coupling medium layer provides a smooth transition of acoustic impedance, allowing ultrasonic energy to be efficiently transmitted from the array to the surface to be connected and the response acoustic signal carrying state information to be efficiently guided back to the receiving element, greatly improving signal transmission efficiency and quality.

[0027] As a specific implementation method, the coupling medium layer can be made of a material that maintains stable acoustic properties and chemical inertness in high-temperature injection molding environments, such as a highly heat-resistant silicon-based thermally conductive gel or a polymer film with good compatibility with the first component material. Its thickness can be selected as one-quarter of the ultrasonic wavelength used to reduce interface reflection and achieve optimal acoustic matching.

[0028] In an optional embodiment, for step S4 mentioned above, the extracted characteristic acoustic parameters include the rate of change of sound velocity and the sound wave attenuation dispersion characteristics of the ultrasonic waves propagating in the near-surface region of the surface to be joined; based on a pre-established acoustic parameter-molecular chain entanglement mapping relationship, the molecular chain entanglement degree of the surface material of the surface to be joined is obtained by inversion from the rate of change of sound velocity and the sound wave attenuation dispersion characteristics, and the molecular chain entanglement degree is used as the characteristic acoustic parameter; wherein, the rate of change of sound velocity Defined as: ,in, The initial sound velocity of the near-surface region of the surfaces to be joined is given by ultrasound when no interfacial activation energy is applied. The velocity of sound is measured in real time during the application of interfacial activation energy; the attenuation dispersion characteristic of this sound wave is expressed as the rate of change of the attenuation coefficient. Representation, defined as: In the formula, This represents the initial attenuation coefficient of the near-surface region of the surfaces to be joined when no interfacial activation energy is applied. The attenuation coefficient is measured in real time during the application of interfacial activation energy; the degree of molecular chain entanglement is... Obtained by inversion of the mapping relationship, and defined as: ,in, For the pre-calibrated acoustic parameter-molecular chain entanglement degree mapping function, The numerical value characterizes the degree of molecular chain entanglement of the surface material to be joined. A decrease in the value indicates an increase in the degree of deentanglement of the molecular chains. The original acoustic measurements (sound velocity, attenuation) are further processed into the rate of change of sound velocity. and the rate of change of attenuation coefficient Instead of directly using absolute sound velocity or absolute attenuation values, this effectively eliminates initial static deviations caused by material batch variations, static environmental temperature fluctuations, and part processing tolerances, allowing these two parameters to more purely reflect the dynamic state changes introduced by interface activation energy. Based on this, a pre-calibrated mapping function... The two-dimensional acoustic parametric variation spectrum is reduced to a one-dimensional molecular chain entanglement degree with clear physical meaning. This simplifies the determination of a material's state from indirect, multi-dimensional acoustic feature comparisons to focusing on a single intrinsic physical quantity of the material. The direct threshold determination greatly facilitates the implementation of the determination logic in the subsequent step S5. The mapping relationship here can be a multidimensional lookup table built based on a large amount of experimental data, or it can be a trained neural network model.

[0029] As a specific implementation method, the calibration process can be carried out as follows: Prepare a series of polymer samples with the same material as the first molded body. By controlling different heating temperatures and holding times, they are brought to viscoelastic states representing different degrees of deentanglement. A rotational rheometer is used to perform frequency scanning tests on each sample, determining its storage modulus and loss modulus at specific temperatures and frequencies. The absolute molecular chain entanglement density value corresponding to each sample is calculated using tube model theory, and this value is used as a label for the true entanglement state. Simultaneously, the same testing conditions are applied to each sample using the same firmware dielectric wave sensor, and its data are collected. and Data. The collected data , The data and corresponding tangle density labels are input into a support vector regression machine or Gaussian process regression model for training, and the mapping function can be obtained. Ultimately, the molecular chain entanglement degree will be used in specific scenarios. Defined as a normalized value, that is, the percentage of the actual entanglement density relative to the initial inactive state entanglement density, such that... The values ​​are dimensionless between 0 and 1, making it easy to set thresholds.

[0030] In one embodiment, regarding step S5 mentioned above, the preset acoustic parameter threshold representing the optimal activation state is a molecular chain entanglement threshold range, which corresponds to the viscoelastic state window where the molecular chains in the surface material of the surface to be joined are partially unentangled but have not undergone irreversible flow; when the molecular chain entanglement obtained by inversion falls within the molecular chain entanglement threshold range, it is determined that the surface to be joined has reached the optimal activation state; wherein, the determination condition for the optimal activation state is: ,in, The degree of molecular chain entanglement obtained by inversion, This represents the lower limit of the threshold range for the degree of entanglement of the molecular chains. This is the upper limit of the molecular chain entanglement threshold range. Corresponding to this viscoelastic window; when When the above determination conditions are met, the surface to be connected is determined to have reached the optimal activation state, triggering the cooperative operation in step S6.

[0031] By setting a range rather than a single fixed value as the threshold, the control logic aligns with the nature of material physical state transitions. The viscoelastic state of polymers is not an abrupt change point, but rather a continuous temperature / energy window. Within this window, the weld quality significantly affects… The system is insensitive to minute fluctuations in the threshold value, exhibiting consistently excellent performance. Therefore, employing a range-based determination method enhances the system's tolerance to minor environmental disturbances (such as small local differences in mold temperature) and sensor noise, preventing false triggering or failure to trigger due to overly stringent thresholds, thus improving control stability and yield. Determining this threshold range requires comprehensive consideration of the relationship between the material's rheological properties and interfacial bonding strength.

[0032] As a specific implementation method, for PC materials, It can be set to 0.7. It can be set to 0.85. Experiments have verified that when the entanglement degree of molecules on the PC surface... When the strength drops to 0.85, the surface molecular chains possess significant diffusion capabilities. At this point, when fused with the second component material, the interfacial lap shear strength can reach over 60% of the original material's bulk strength. As activation continues, the entanglement degree... When the strength drops to 0.7, the weld strength reaches its peak, approaching the body strength. Further activation... Below 0.7, although the molecular chain mobility is extremely high, some short-chain molecules on the surface begin to undergo irreversible thermal relaxation flow, leading to microscopic defects and molecular chain orientation at the surface and interface. As a result, the dispersion of the weld strength begins to increase, and the average strength begins to decrease. Therefore, the interval [0.7, 0.85] is determined to be a "viscoelastic window" that can both ensure sufficient molecular diffusion welds and effectively avoid the risk of overactivation.

[0033] In one experiment, fifty PC / PC-ABS overlap shear splines were prepared using the method of this embodiment. Twenty-five of these splines employed the adaptive cooperative control method of this invention. Injection was automatically triggered when the value entered the [0.7, 0.85] range; another twenty-five splines served as a control group, using laser activation for a fixed duration (1.5 seconds). Experimental results showed that the splines prepared using this method exhibited an average lap shear strength of 42.1 MPa and a standard deviation of 1.1 MPa, demonstrating extremely high strength and excellent consistency. In contrast, the control group splines had an average strength of only 35.6 MPa and a standard deviation as high as 4.5 MPa. Scanning electron microscopy analysis of the failure interface revealed that the fracture surface of the adaptive group exhibited typical ductile tearing, indicating cohesive failure; while the fracture surface of the control group showed brittle fracture characteristics in some areas, indicating interfacial bonding failure, confirming the significant improvement of interfacial welding quality by adaptive control.

[0034] In an optional embodiment, the application of interface activation energy to the surfaces to be joined of the first molded body in step S2 is achieved through laser pulse heating. This interface activation energy is applied as a modulated energy pulse waveform, which includes various waveforms with different pulse widths and peak powers. The parameters of this energy pulse waveform are adaptively set according to the pattern characteristics of the surfaces to be joined of the first molded body. Laser pulse heating allows for precise spatial and temporal control and programming of energy, offering advantages such as non-contact operation, fast response, and good area selection. Modulating the interface activation energy into a specific waveform, rather than a continuous wave, enables precise "tailoring" of the temperature field at the material's surface and subsurface. By flexibly changing the combination of pulse width and peak power, the depth of the heat-affected zone and the spatial distribution of the temperature gradient can be controlled.

[0035] Furthermore, by adaptively setting waveform parameters based on the characteristics of the surface to be connected, such as the presence or absence of patterns and the density of patterns, it is possible to ensure that different regions absorb light energy to different degrees, but the heating effect is consistent. This avoids uneven activation caused by differences in specific heat capacity or light absorption efficiency between flat areas and areas with microstructures, and ensures the uniformity of the activation state of the entire surface to be connected in space.

[0036] As a specific implementation, the laser used can be a semiconductor laser array (wavelength 980nm or 1064nm) with high electro-optical conversion efficiency and a compact structure. After homogenization and shaping, its beam can form a uniformly energetic linear or rectangular spot projected onto the surface to be joined. Waveform modulation is achieved through a high-speed pulse width modulation current driver based on a field-programmable gate array (FPGA). Its pulse modulation frequency can reach 100kHz, and the pulse width and peak current can be arbitrarily programmed with a resolution of 10 microseconds and 1 ampere.

[0037] In one embodiment, regarding the aforementioned modulated energy pulse waveform, when the surface to be joined of the first molded body includes a light-shielding pattern area, the light-shielding pattern area includes a fine line area with a first linewidth and a surface area with a second linewidth, the first linewidth being smaller than the second linewidth; a first energy pulse waveform is applied to the fine line area, and a second energy pulse waveform is applied to the surface area, the pulse width of the first energy pulse waveform being smaller than the pulse width of the second energy pulse waveform, and the peak power of the first energy pulse waveform being greater than the peak power of the second energy pulse waveform. The principle of this differentiated waveform setting is "narrow and high pulses for small areas, and wide and low pulses for large areas." The underlying mechanism lies in the different rates of heat accumulation and dissipation due to the different geometric dimensions. Due to its small volume and large surface area-to-volume ratio, the fine line area is easily dissipated by heat through conduction to the surrounding substrate material in a short time. Therefore, a first waveform with high peak power and narrow pulse width is required to inject energy at extremely high density in a very short time, rapidly raising the surface layer of the fine line area to a viscoelastic temperature before a large amount of heat is dissipated. Conversely, for large surface areas, which have high heat capacity and relatively slow heat dissipation, using narrow peak pulses can easily create localized hot spots. Therefore, employing a second waveform with lower peak power and a wider pulse width allows energy to be injected at a relatively gentle rate over a longer period, enabling the temperature of the entire surface area to rise uniformly and synchronously, thus avoiding overheating. This adaptive modulation strategy ensures that on surfaces with complex geometric patterns, the activation states of different feature regions tend to reach synchronous levels in time, ultimately allowing the entire surface to synchronously enter the optimal activation state window, creating conditions for the unified and coordinated operation in the subsequent step S6.

[0038] As a specific implementation, the two-dimensional galvanometer scanning system is linked with a field-programmable gate array (FPGA) controller that controls the modulation waveform of the laser pulses. The system first obtains the pattern features of the surfaces to be connected from the computer-aided design file of the mold, and then classifies each scanning path point into graphic categories (fine lines / surface areas). When the galvanometer scans to a fine line area, the FPGA instantly switches the output of the first energy pulse waveform (e.g., peak power 200W, pulse width 100 microseconds); when scanning to a surface area, it instantly switches to the second energy pulse waveform (e.g., peak power 50W, pulse width 500 microseconds), achieving adaptive dynamic modulation of the waveform based on the area's location.

[0039] In an optional embodiment, the operation of injecting the second component material in step S6 mentioned above is triggered in real time based on a signal from the solid-state dielectric wave sensor indicating that the optimal activation state has been reached. In the initial stage of injecting the second component material, injection is performed using a creeping filling speed curve, allowing the leading edge of the second component material to contact the surface to be joined in a laminar flow state, achieving molecular-level diffusion fusion. Real-time triggering based on the feedback signal from the solid-state dielectric wave sensor, rather than based on a preset fixed delay, is the core of achieving "adaptive" collaboration. It ensures that the start time of the injection operation is closely tied to the actual physical state of the material. Based on this, a creeping filling speed curve is used in the initial stage of injection, meaning the injection speed is performed in one or more small-amplitude advance, pause, and then advance pulse-like movements. This filling mode avoids the jetting phenomenon at the gate or unstable turbulence at the melt leading edge that occurs with traditional high-speed injection, which can entrain air or cause erosion of the softened surface. The slow propagation under laminar flow conditions allows the high-temperature melt front of the second component material to conduct stable and continuous heat exchange and molecular chain diffusion with the entire surface to be joined. Sufficient contact and wetting at the molecular scale are the physical prerequisites for achieving high-strength diffusion welding. This synergistic combination ensures the ultimate welding quality from two dimensions: "time window" and "contact mode".

[0040] As a specific implementation of the peristaltic filling rate curve, an injection system equipped with a high-response servo valve can be used. During the initial injection phase, the screw operates at a relatively low base speed. Begin advancing, pausing for a preset short time (e.g., 50 milliseconds) after advancing a small distance (e.g., 0.5mm), then continue advancing. Proceed to the next stage, repeating this process until the melt front completely covers the surface area to be joined, then switch to the regular high-speed filling stage to complete the filling of the remaining cavity.

[0041] In an optional embodiment, for the aforementioned scheme, the first component material is a thermoplastic polymer containing a latent reaction aid, which is dispersed in the surface region of the first component material in the form of microcapsules. In step S2, the applied interfacial activation energy is set to simultaneously satisfy the energy conditions for rupturing the microcapsules and activating the latent reaction aid, such that in step S6, when the second component material comes into contact with the surface to be joined, the latent reaction aid initiates a chemical bonding reaction in situ at the interface. In addition to physical diffusion and molecular chain entanglement, this scheme introduces chemical bonding at the interface, forming a hybrid interface with both physical and chemical anchoring, which can geometrically improve the interfacial bonding strength and long-term durability (such as resistance to damp heat aging) of the final composite. Latentifying the reaction aid (e.g., microcapsule encapsulation) is to prevent it from prematurely reacting and failing in the high-temperature shear environment of the first component material plasticizing and injection molding first stage (step S1). By integrating the energy required to rupture microcapsules and activate the adjuvant into the activation energy of step S2, a clever "two birds with one stone" utilization of energy is achieved. Without adding extra process steps or equipment, the chemical reaction is triggered only at the required time and spatial point (i.e., at the interface to be connected). In step S6, when the activated molecular chains of the second component material come into contact with and diffuse into the surface of the first component, the reaction occurs in situ at the interface, and the resulting chemical bonds cross the interface, forming a robust "molecular bridge."

[0042] As a specific implementation method, the first component material is polybutylene terephthalate (PET), in which microcapsules, accounting for approximately 2-5% of the mass of the near-surface layer (approximately 50-100 micrometers thick), are uniformly dispersed through a secondary injection or blending process. The wall material of the microcapsules can be urea-formaldehyde resin, and the core material can be a latent epoxy curing agent. In step S2, laser pulse heating is used to instantly raise the near-surface layer temperature to the thermal cracking temperature of the microcapsule wall material (e.g., above 200°C) and the thermal activation temperature of the curing agent. This causes the hydroxyl groups at the ends of the polycarbonate of the second component material to undergo an in-situ curing and crosslinking reaction upon interface contact in step S6, generating a strong chemically bonded interface.

[0043] In an optional embodiment, for the overall scheme described above, the control method further includes step S7 after step S6: Repeating steps S2 to S6 on the surfaces to be joined of the composite formed by the first molded body and the second component materials that have already been fused, and after monitoring and determining that the surface to be joined has reached its optimal activation state using the solid-state dielectric wave sensing device, triggering the injection of the third component material, so that the third component material contacts and fuses with the surface to be joined of the composite in its optimal activation state; the first component material is transparent polycarbonate, the second component material is a black opaque polycarbonate / acrylonitrile-butadiene-styrene copolymer alloy, and the third component material is a semi-transparent thermoplastic polyurethane, used for molding automotive interior ambient lighting panels. This embodiment seamlessly extends the control logic of the present invention to the fusion of multiple components with two or more layers, fully demonstrating its modularity and scalability advantages. By iteratively applying the "perception-determination-execution" closed loop, the fusion of each new material layer has independent adaptive optimization capabilities, unaffected by the cumulative impact of physical state fluctuations in previous steps, thereby ensuring that each interface of the final multi-layer composite structure has high quality and high consistency. The material configuration specifically designed for automotive interior ambient lighting panels solves a key challenge in actual product manufacturing: how to achieve a perfect combination of multiple optical and mechanical interfaces between the transparent layer, the opaque light-blocking layer, and the soft-touch light-transmitting layer. Transparent polycarbonate provides structural strength and a light-transmitting substrate, while a black polycarbonate / acrylonitrile-butadiene-styrene copolymer alloy forms a precise light-blocking pattern. Semi-transparent thermoplastic polyurethane imparts a soft touch and gentle light-scattering effect to the outermost layer. By adaptively determining and simultaneously activating and injecting the material before each welding step, defects such as bubbles, delamination, or blurred patterns caused by stress, uneven shrinkage, or weak bonding between layers can be avoided.

[0044] In a specific application example, this method is used to produce thin-walled automotive ambient light panels with a thickness of only 2 mm. In the first step, optical-grade transparent PC is injection molded into a first molded body with a contoured surface. Then, using the synergistic control method described in all the above embodiments, black PC / ABS is precisely fused to its back side to form a light-shielding pattern. Finally, for the exposed surfaces of the molded PC and PC / ABS composite, steps S2 to S6 are repeated to fuse a translucent thermoplastic polyurethane onto them. The entire process requires only one in-mold transfer, without the need for additional processing after removing the part. Peel strength testing of the final product shows that the failure occurs within the thermoplastic polyurethane base material, rather than at the interlayer interface, and after a thermal shock cycling aging test at -40°C to 85°C for 1000 hours, no obvious cracks or delamination are observed at the interface, and light transmittance uniformity remains good.

[0045] To facilitate understanding of the technical solution of this invention, the key terms involved are explained as follows: First molded part: refers to the part obtained by injection molding of the first component material in the first step of multi-component injection molding, which serves as the base for subsequent welding operations.

[0046] Interface activation energy: refers to the energy applied to the surface of the first molded body to be joined, which is used to change the thermodynamic state of the molecular chains of the material in the near-surface region. Its purpose is to transform the polymer chains from a rigid glassy state or a highly elastic state to a viscoelastic state, thereby increasing the mobility of the chain segments.

[0047] Viscoelastic state: refers to a physical state of polymer materials, between the solid and liquid states. In this state, the material exhibits some characteristics of an elastic solid (deformation can be partially recovered) and also exhibits characteristics of a viscous liquid (molecular chains can undergo relative slippage). Within this window, the molecular chains have acquired sufficient mobility to achieve cross-interface diffusion and entanglement, but irreversible macroscopic flow has not yet occurred, making it an ideal state for interfacial welding.

[0048] Solid medium wave sensing device: refers to a device that uses the changes in the propagation characteristics of elastic waves such as sound waves or ultrasonic waves in a solid medium (specifically, the first molded body and its near-surface region) to sense changes in the physical state of the material.

[0049] Characteristic acoustic parameters: These are specific acoustic quantities extracted from the received response acoustic wave signals that can quantitatively or semi-quantitatively reflect the changes in the physical properties (such as stiffness, density, damping, degree of molecular chain entanglement, etc.) of the surface materials to be joined.

[0050] Molecular chain entanglement: refers to a physical quantity used to quantify the degree of entanglement and knotting between molecular chains inside and on the surface of polymer materials. Its numerical change directly reflects the evolution of the microstructure of polymer materials.

[0051] Example 2: An adaptive collaborative control system for multi-component injection molding, comprising: The first injection module is used to inject the first component material and mold it into a first molded body with a surface to be connected. The activation module is used to apply interfacial activation energy to the surfaces to be joined of the first molded body, so that the surface material of the surfaces to be joined is transformed into a viscoelastic state. The sensing module is used to emit acoustic wave signals to the surface to be connected during the application of interface activation energy, and to receive the response acoustic wave signals propagating through the surface to be connected. The parameter extraction module is used to extract characteristic acoustic parameters that reflect the entanglement state of molecular chains of the surface material to be connected, based on the response acoustic wave signal. The determination module is used to compare the characteristic acoustic parameters with preset acoustic parameter thresholds that characterize the optimal activation state. When the characteristic acoustic parameters reach the acoustic parameter thresholds, it is determined that the surface to be connected has reached the optimal activation state. The collaborative execution module is used to synchronously perform the following operations: terminate the application of interfacial activation energy to the surfaces to be joined, and trigger the injection of the second component material, so that the second component material contacts and fuses with the surfaces to be joined in the optimal activation state.

[0052] Example 3: An electronic device includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement an adaptive collaborative control method for multi-component injection molding.

[0053] Example 4: A computer-readable storage medium storing a computer program that, when executed by a processor, implements an adaptive collaborative control method for multi-component injection molding.

[0054] Example 5: To verify the effectiveness of the method of the present invention, a complete molding verification test was conducted using transparent polycarbonate (PC) as the first component material and black polycarbonate / acrylonitrile-butadiene-styrene copolymer alloy (PC / ABS) as the second component material, following steps S1 to S6. The main process conditions and material parameters used in the test are listed in the table below:

[0055] The verification process is as follows: First, step S1 is performed, where molten transparent polycarbonate is injected into the mold cavity. After pressure holding and cooling, it is molded into a first molded body with the surfaces to be joined. The surfaces to be joined are smooth, flat areas without any patterns.

[0056] Then, step S2 is executed, activating the laser pulse heating device to apply interface activation energy to the surface of the first molded body to be joined. The laser operates in continuous pulse mode, with a fixed single pulse energy of 0.5J and a pulse repetition frequency of 20Hz, continuing heating until terminated by a subsequent determination step.

[0057] While applying interface activation energy, the solid dielectric wave sensing device is activated in step S3. This device is an aluminum nitride piezoelectric microelectromechanical system ultrasonic transceiver array, which is acoustically coupled to the surface to be joined of the first molded body through a coupling dielectric layer. The transmitting element in the array simultaneously excites 30MHz ultrasonic transverse and longitudinal waves, and the receiving element receives the response ultrasonic signal propagating through the near-surface region of the surface to be joined at a sampling rate of 1000 times per second, and transmits it to the signal processing unit.

[0058] In step S4, the signal processing unit extracts the sound velocity and attenuation coefficient from the received ultrasonic signal in real time. The average value of 100 sets of data collected before applying the interface activation energy is used as the initial sound velocity. and initial attenuation coefficient Then, the rate of change of sound speed was calculated point by point. and the rate of change of attenuation coefficient Then through a pre-defined mapping function Inverting molecular chain entanglement The data was recorded every 0.2 seconds during the experiment. The values, and representative data, are listed in the table below:

[0059] Following step S5, the molecular chain entanglement degree obtained from the real-time inversion is... The value is compared with a preset optimal activation state threshold range. In this embodiment, for the transparent polycarbonate material used, the pre-defined molecular chain entanglement threshold range is: , As can be seen from the above, when the activation time is 0.6 seconds, With a value of 0.835, the value enters the threshold range for the first time, and the control unit immediately determines that the surface to be connected has reached the optimal activation state.

[0060] Within the same control cycle where the determination signal is generated, a coordinated operation is performed according to step S6: the laser pulse heating device is momentarily shut off, and the application of interface activation energy is terminated; simultaneously, the injection screw of the second component material PC / ABS is triggered to start. In the initial injection stage, a creeping filling speed curve is used, with the screw advancing at a base speed of 5 mm / s, pausing for 50 ms after every 0.5 mm advance, and waiting for the melt front to cover the entire surface to be joined in a laminar flow state before switching to a conventional speed of 80 mm / s to complete cavity filling.

[0061] To compare and verify the advantages of adaptive collaborative control, a control group with a fixed activation time of 1.2 seconds was used to form identical parts. Twenty parts were prepared from each group, and the lap shear strength was tested according to ISO 527 standard. The interfaces were observed using scanning electron microscopy. The test results are listed in the table below:

[0062] As shown in the table above, the average lap shear strength of the adaptive collaborative control group was approximately 24.5% higher than that of the control group, and the strength standard deviation was significantly reduced, indicating a significant improvement in interface welding quality and excellent consistency. All interface failure modes were cohesive failure, proving that the welded interface strength exceeded the material bulk strength. In contrast, the fixed activation time control group showed partial interface adhesion failure and large strength dispersion. This verification example fully demonstrates the significant technical effect of the method of the present invention in accurately capturing the optimal activation window and achieving high-strength, reliable welding.

[0063] The embodiments disclosed in this invention are preferred embodiments, but are not limited thereto. Those skilled in the art can easily understand the spirit of this invention based on the above embodiments and make different extensions and variations, but as long as they do not depart from the spirit of this invention, they are all within the protection scope of this invention.

Claims

1. An adaptive collaborative control method for multi-component injection molding, characterized in that, include: Inject the first component material to form a first molded body with the surfaces to be joined; Interfacial activation energy is applied to the surfaces of the first molded body to be joined, causing the surface material of the surfaces to be joined to transform into a viscoelastic state; During the process of applying interfacial activation energy, a solid-state dielectric wave sensing device transmits acoustic wave signals to the surface to be connected and receives the response acoustic wave signals propagating through the surface to be connected. Based on the response acoustic signal, characteristic acoustic parameters reflecting the molecular chain entanglement state of the surface material to be connected are extracted. The characteristic acoustic parameters are compared with preset acoustic parameter thresholds that characterize the optimal activation state. When the characteristic acoustic parameters reach the acoustic parameter thresholds, it is determined that the surface to be connected has reached the optimal activation state. The following operations are performed simultaneously: the application of interfacial activation energy to the surfaces to be joined is terminated, and the injection of the second component material is triggered, so that the second component material contacts and fuses with the surfaces to be joined in the optimal activation state.

2. The adaptive collaborative control method for multi-component injection molding according to claim 1, characterized in that, The solid-state dielectric wave sensing device is a piezoelectric microelectromechanical system ultrasonic transceiver array, which transmits acoustic wave signals to the surface to be connected and receives response acoustic wave signals propagating through the surface to be connected, including: The ultrasonic transverse and longitudinal waves of the piezoelectric microelectromechanical system are emitted to the surface to be connected by an ultrasonic transceiver array, and the response ultrasonic signals propagating through the near-surface region of the surface to be connected are received.

3. The adaptive collaborative control method for multi-component injection molding according to claim 2, characterized in that, The extraction of characteristic acoustic parameters reflecting the entanglement state of molecular chains in the surface material to be joined includes: The ultrasonic velocity change rate and acoustic attenuation dispersion characteristics are extracted from the response ultrasonic signal. Based on the pre-established acoustic parameter-molecular chain entanglement mapping relationship, the molecular chain entanglement degree of the surface material to be joined is obtained by inversion, and the molecular chain entanglement degree is used as a characteristic acoustic parameter.

4. The adaptive collaborative control method for multi-component injection molding according to claim 3, characterized in that, The preset acoustic parameter threshold for characterizing the optimal activation state is a molecular chain entanglement threshold range, which corresponds to the viscoelastic state window where the molecular chains of the surface material to be connected are partially unentangled but have not undergone irreversible flow. When the molecular chain entanglement degree obtained by inversion falls within the molecular chain entanglement degree threshold range, it is determined that the surface to be connected has reached the optimal activation state.

5. The adaptive collaborative control method for multi-component injection molding according to claim 1, characterized in that, Applying interfacial activation energy to the surfaces to be joined of the first molded body includes: A modulated laser pulse energy is applied to the surfaces to be joined. The pulse waveform of the laser pulse energy is adaptively set according to the pattern characteristics of the surfaces to be joined. The pulse waveform includes pulse width and peak power parameters.

6. The adaptive collaborative control method for multi-component injection molding according to claim 5, characterized in that, When the surface to be connected includes a thin line region with a line width less than a preset value and a surface region with a line width greater than a preset value, a first pulse waveform is applied to the thin line region and a second pulse waveform is applied to the surface region. The pulse width of the first pulse waveform is less than the pulse width of the second pulse waveform, and the peak power of the first pulse waveform is greater than the peak power of the second pulse waveform.

7. The adaptive collaborative control method for multi-component injection molding according to claim 1, characterized in that, The trigger injection of the second component material includes: In the initial stage of injection, a peristaltic filling rate curve is used to make the melt front of the second component material contact the surface to be joined in a laminar flow state, thereby achieving molecular-level diffusion welding.

8. An adaptive collaborative control system for multi-component injection molding, characterized in that, include: The first injection module is used to inject the first component material and mold it into a first molded body with a surface to be connected. The activation module is used to apply interfacial activation energy to the surfaces to be joined of the first molded body, so that the surface material of the surfaces to be joined is transformed into a viscoelastic state. The sensing module is used to emit acoustic wave signals to the surface to be connected during the application of interface activation energy, and to receive the response acoustic wave signals propagating through the surface to be connected. The parameter extraction module is used to extract characteristic acoustic parameters that reflect the entanglement state of molecular chains of the surface material to be connected, based on the response acoustic wave signal. The determination module is used to compare the characteristic acoustic parameters with preset acoustic parameter thresholds that characterize the optimal activation state. When the characteristic acoustic parameters reach the acoustic parameter thresholds, it is determined that the surface to be connected has reached the optimal activation state. The collaborative execution module is used to synchronously perform the following operations: terminate the application of interfacial activation energy to the surfaces to be joined, and trigger the injection of the second component material, so that the second component material contacts and fuses with the surfaces to be joined in the optimal activation state.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the adaptive collaborative control method for multi-component injection molding as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the adaptive collaborative control method for multi-component injection molding as described in any one of claims 1 to 7.

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